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Autoreducibility of Random Sets: A Sharp Bound on the Density of Guessed Bits

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Book cover Mathematical Foundations of Computer Science 2002 (MFCS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2420))

Abstract

A set A ⊆ 0,1* is called i.o. Turing-autoreducible if A is reducible to itself via an oracle Turing machine that never queries its oracle at the current input, outputs either A(x) or a don’t-know symbol on any given input x, and outputs A(x) for infinitely many x. If in addition the oracle Turing machine terminates on all inputs and oracles, A is called i.o. truth-table autoreducible. Ebert and Vollmer obtained the somewhat counterintuitive result that every Martin-Löf random set is i.o. truth-table-autoreducible and investigated the question of how dense the set of guessed bits can be when i.o. autoreducing a random set.

We show that rec-random sets are never i.o. truth-table-autoreducible such that the set of guessed bits has strictly positive constant density in the limit, and that a similar assertion holds for Martin-Löf random sets and i.o. Turing-autoreducibility. On the other hand, our main result asserts that for any computable function r that goes non-ascendingly to zero, any rec-random set is i.o. truth-table-autoreducible such that the set of guessed bits has density bounded from below by r(m).

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References

  1. K. Ambos-Spies and A. Kučera. Randomness in computability theory. In P. A. Cholak et al. (eds.), Computability theory and its applications. Current trends and open problems. Proceedings of a 1999 AMS-IMS-SIAM joint summer research conference, Boulder, USA, AMS Contemporary Mathematics 257:1–14, 2000.

    Google Scholar 

  2. K. Ambos-Spies and E. Mayordomo. Resource-bounded measure and randomness. In A. Sorbi (ed.), Complexity, logic, and recursion theory, p. 1–47. Dekker, New York, 1997.

    Google Scholar 

  3. J. Aspnes, R. Beigel, M. Furst, and S. Rudich. The expressive power of voting polynomials, Combinatorica 14(2), p. 135–148, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  4. J. L. Balcázar, J. Díaz, and J. Gabarró. Structural Complexity, volumes I and II. Springer, 1995 and 1990.

    Google Scholar 

  5. H. Buhrman, L. Fortnow, D. van Melkebeek, and L. Torenvliet, Separating complexity classes using autoreducibility. SIAM Journal on Computing 29:1497–1520, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  6. H. Buhrman, D. van Melkebeek, K. W. Regan, D. Sivakumar, M. Strauss, A generalization of resource-bounded measure, with application to the BPP vs. EXP problem. SIAM Journal on Computing 30(2):576–601, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  7. T. Ebert. Applications of Recursive Operators to Randomness and Complexity. Ph.D. Thesis, University of California at Santa Barbara, 1998.

    Google Scholar 

  8. T. Ebert, H. Vollmer. On the Autoreducibility of Random Sequences. In: M. Nielsen and B. Rovan (eds.), Mathematical Foundations of Computer Science 2000, Lecture Notes in Computer Science 1893: 333–342, Springer, 2000.

    Chapter  Google Scholar 

  9. M. Li and P. Vitányi. An Introduction to Kolmogorov Complexity and Its Applications, second edition. Springer, 1997.

    Google Scholar 

  10. J. H. Lutz. Almost everywhere high nonuniform complexity. Journal of Computer and System Sciences, 44:220–258, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  11. J. H. Lutz. The quantitative structure of exponential time. In L. A. Hemaspaandra and A. L. Selman (eds.), Complexity Theory Retrospective II, p. 225–260, Springer, 1997.

    Google Scholar 

  12. P. Martin-Löf. The definition of random sequences. Inform. and Control 9(6):602–619, 1966.

    Article  Google Scholar 

  13. E. Mayordomo. Contributions to the Study of Resource-Bounded Measure. Doctoral dissertation, Universitat Politècnica de Catalunya, Barcelona, Spain, 1994.

    Google Scholar 

  14. W. Merkle and N. Mihailović. On the construction of effective random sets. In: Mathematical Foundations of Computer Science 2002, this volume.

    Google Scholar 

  15. P. Odifreddi. Classical Recursion Theory. North-Holland, Amsterdam, 1989.

    Google Scholar 

  16. S. Robinson. Why mathematicians now care about their hat color. NY Times, April 10, 2001.

    Google Scholar 

  17. C.-P. Schnorr. A unified approach to the definition of random sequences. Mathematical Systems Theory, 5:246–258, 1971.

    Article  MATH  MathSciNet  Google Scholar 

  18. R. I. Soare. Recursively Enumerable Sets and Degrees. Springer, 1987.

    Google Scholar 

  19. S. A. Terwijn. Computability and Measure. Doctoral dissertation, Universiteit van Amsterdam, Amsterdam, Netherlands, 1998.

    Google Scholar 

  20. B. A. Trakhtenbrot, On Autoreducibility. Soviet Math. Doklady, 11:814–817, 1970.

    MATH  Google Scholar 

  21. J.H. van Lint. Introduction to coding theory, third edition. Springer, 1999.

    Google Scholar 

  22. K. Wagner and G. Wechsung. Computational Complexity. Deutscher Verlag der Wissenschaften, Berlin, 1986.

    Google Scholar 

  23. Y. Wang. Randomness and Complexity. Doctoral dissertation, Universität Heidelberg, Mathematische Fakultät, INF 288, Heidelberg, Germany, 1996.

    MATH  Google Scholar 

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Ebert, T., Merkle, W. (2002). Autoreducibility of Random Sets: A Sharp Bound on the Density of Guessed Bits. In: Diks, K., Rytter, W. (eds) Mathematical Foundations of Computer Science 2002. MFCS 2002. Lecture Notes in Computer Science, vol 2420. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45687-2_18

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  • DOI: https://doi.org/10.1007/3-540-45687-2_18

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